{
  "fetched_at": "2026-10-20T00:52:50Z",
  "source_url": "https://www.kaggle.com/competitions/dsc-iba-datathon/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n<hr>\n<h2>Data fields</h2>\n<ul>\n<li>ID_Patient_Care_Situation: Care situation of a patient during treatment</li>\n\n<li>Diagnosed_Condition: The diagnosed condition of the patient</li>\n\n<li>ID_Patient: Patient identifier number</li>\n\n<li>Treatment_with_drugs: Class of drugs used during treatment</li>\n\n<li>Survived_1_year: If the patient survived after one year (0 means did not survive; 1 means survived)</li>\n\n<li>Patient_Age: Age of the patient</li>\n\n<li>Patient_Body_Mass_Index: A calculated value based on the patient’s weight, height, etc.</li>\n\n<li>Patient_Smoker: If the patient was a smoker or not</li>\n\n<li>Patient_Rural_Urban: If the patient stayed in Rural or Urban part of the country</li>\n</ul>\n\nPrevious_Condition: Condition of the patient before the start of the treatment ( This variable is splitted into 8 columns - A, B, C, D, E, F, Z and Number_of_prev_cond. A, B, C, D, E, F and Z are the previous conditions of the patient. Suppose for one patient, if the entry in column A is 1, it means that the previous condition of the patient was A. If the patient didn't have that condition, it is 0 and same for other conditions. If a patient has previous condition as A and C , columns A and C will have entries as 1 and 1 respectively while the other column B, D, E, F, Z will have entries 0, 0, 0, 0, 0 respectively. The column Number_of_prev_cond will have entry as 2 i.e. 1 + 0 + 1 + 0 + 0 + 0 + 0 + 0 = 2 in this case. )\n\n<p><strong>Feel free to google 'Diagnose' and 'Body Mass Index' if you don't know about these terms.</strong></p>",
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    {
      "name": "Description",
      "content": "<h1>About</h1>\n<p>A hospital in the province of Greenland has been trying to improve its care conditions by looking at historic survival of the patients. They tried looking at their data but could not identify the main factors leading to high survival.</p>\n<h1>Objective</h1>\n<p>You are the best data scientist in Greenland and they've hired you to solve this problem. Now you are responsible for developing a model that will predict the chances of survival of a patient after 1 year of treatment (Survived_1_year).</p>\n<h2>Good Luck :)</h2>",
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    {
      "name": "Evaluation",
      "content": "<p></p><p>Submissions are evaluated using the F1 Score. How do we do it? \n\nOnce you generate and submit the target variable predictions on evaluation dataset, your submissions will be compared with the true values of the target variable. \n\nThe True or Actual values of the target variable are hidden on the platform so that we can evaluate your model's performance on evaluation data. Finally, an F1 score for your model will be generated and displayed</p>\n<p></p>\n<hr>",
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    },
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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